A neural network–based sliding mode controller of folding-boom aerial work platform

Aerial work platform is a special vehicle for carrying personnel to the appointed site in the air for operations. Therefore, the work platform requires high stability. This article proposes a sliding mode controller based on neural network for tracking control of folding-boom aerial work platform. S...

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Main Authors:	Haidong Hu, Ning Cai, Lizhen Cui, Yan Ren, Wensheng Yu
Format:	Article
Language:	English
Published:	SAGE Publishing 2017-10-01
Series:	Advances in Mechanical Engineering
Online Access:	https://doi.org/10.1177/1687814017720876

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spelling	doaj-aef3d4a2923041dea18d30ee56b8676e2020-11-25T03:51:59ZengSAGE PublishingAdvances in Mechanical Engineering1687-81402017-10-01910.1177/1687814017720876A neural network–based sliding mode controller of folding-boom aerial work platformHaidong Hu0Ning Cai1Lizhen Cui2Yan Ren3Wensheng Yu4School of Information Engineering, Inner Mongolia University of Science & Technology, Baotou, ChinaCollege of Electrical Engineering, Northwest University for Nationalities, Lanzhou, ChinaSchool of Information Engineering, Inner Mongolia University of Science & Technology, Baotou, ChinaSchool of Information Engineering, Inner Mongolia University of Science & Technology, Baotou, ChinaSchool of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, ChinaAerial work platform is a special vehicle for carrying personnel to the appointed site in the air for operations. Therefore, the work platform requires high stability. This article proposes a sliding mode controller based on neural network for tracking control of folding-boom aerial work platform. Since the chattering caused by sliding mode controller with high-speed switching control may lead to system performance degradation, continuous control obtained from neural network system replaces discontinuous switching control to eliminate chattering. Furthermore, the whole system is proved to be stable by Lyapunov stability theorem. Finally, numerical results show that the designed controller can eliminate the chattering resulting from switching control in sliding mode controller and inhibit the vibration of work platform when there exists system uncertainty. Moreover, the controller is effective for the reduction of tracking error.https://doi.org/10.1177/1687814017720876
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Haidong Hu Ning Cai Lizhen Cui Yan Ren Wensheng Yu
spellingShingle	Haidong Hu Ning Cai Lizhen Cui Yan Ren Wensheng Yu A neural network–based sliding mode controller of folding-boom aerial work platform Advances in Mechanical Engineering
author_facet	Haidong Hu Ning Cai Lizhen Cui Yan Ren Wensheng Yu
author_sort	Haidong Hu
title	A neural network–based sliding mode controller of folding-boom aerial work platform
title_short	A neural network–based sliding mode controller of folding-boom aerial work platform
title_full	A neural network–based sliding mode controller of folding-boom aerial work platform
title_fullStr	A neural network–based sliding mode controller of folding-boom aerial work platform
title_full_unstemmed	A neural network–based sliding mode controller of folding-boom aerial work platform
title_sort	neural network–based sliding mode controller of folding-boom aerial work platform
publisher	SAGE Publishing
series	Advances in Mechanical Engineering
issn	1687-8140
publishDate	2017-10-01
description	Aerial work platform is a special vehicle for carrying personnel to the appointed site in the air for operations. Therefore, the work platform requires high stability. This article proposes a sliding mode controller based on neural network for tracking control of folding-boom aerial work platform. Since the chattering caused by sliding mode controller with high-speed switching control may lead to system performance degradation, continuous control obtained from neural network system replaces discontinuous switching control to eliminate chattering. Furthermore, the whole system is proved to be stable by Lyapunov stability theorem. Finally, numerical results show that the designed controller can eliminate the chattering resulting from switching control in sliding mode controller and inhibit the vibration of work platform when there exists system uncertainty. Moreover, the controller is effective for the reduction of tracking error.
url	https://doi.org/10.1177/1687814017720876
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A neural network–based sliding mode controller of folding-boom aerial work platform

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